little modify

3 files changed, 11 insertions, 12 deletions

diff --git a/become_yukarin/config.py b/become_yukarin/config.py
index f74c83e..424e598 100644
--- a/become_yukarin/config.py
+++ b/become_yukarin/config.py
@@ -9,8 +9,8 @@ from .param import Param
 
 class DatasetConfig(NamedTuple):
     param: Param
-    input_glob: str
-    target_glob: str
+    input_glob: Path
+    target_glob: Path
     input_mean_path: Path
     input_var_path: Path
     target_mean_path: Path
@@ -40,7 +40,6 @@ class TrainConfig(NamedTuple):
     gpu: int
     log_iteration: int
     snapshot_iteration: int
-    output: Path
 
 
 class Config(NamedTuple):
@@ -76,8 +75,8 @@ def create_from_json(s: Union[str, Path]):
     return Config(
         dataset=DatasetConfig(
             param=Param(),
-            input_glob=d['dataset']['input_glob'],
-            target_glob=d['dataset']['target_glob'],
+            input_glob=Path(d['dataset']['input_glob']).expanduser(),
+            target_glob=Path(d['dataset']['target_glob']).expanduser(),
             input_mean_path=Path(d['dataset']['input_mean_path']).expanduser(),
             input_var_path=Path(d['dataset']['input_var_path']).expanduser(),
             target_mean_path=Path(d['dataset']['target_mean_path']).expanduser(),
@@ -104,6 +103,5 @@ def create_from_json(s: Union[str, Path]):
             gpu=d['train']['gpu'],
             log_iteration=d['train']['log_iteration'],
             snapshot_iteration=d['train']['snapshot_iteration'],
-            output=Path(d['train']['output']).expanduser(),
         ),
     )
diff --git a/become_yukarin/dataset/dataset.py b/become_yukarin/dataset/dataset.py
index dc5bc74..633843e 100644
--- a/become_yukarin/dataset/dataset.py
+++ b/become_yukarin/dataset/dataset.py
@@ -97,7 +97,7 @@ class AcousticFeatureProcess(BaseDataProcess):
             spectrogram=spectrogram.astype(self._dtype),
             aperiodicity=aperiodicity.astype(self._dtype),
             mfcc=mfcc.astype(self._dtype),
-            voiced=voiced[:, None].astype(self._dtype),
+            voiced=voiced[:, None],
         )
         feature.validate()
         return feature
@@ -232,8 +232,8 @@ class DataProcessDataset(chainer.dataset.DatasetMixin):
 
 def create(config: DatasetConfig):
     import glob
-    input_paths = list(sorted([Path(p) for p in glob.glob(config.input_glob)]))
-    target_paths = list(sorted([Path(p) for p in glob.glob(config.target_glob)]))
+    input_paths = list(sorted([Path(p) for p in glob.glob(str(config.input_glob))]))
+    target_paths = list(sorted([Path(p) for p in glob.glob(str(config.target_glob))]))
     assert len(input_paths) == len(target_paths)
 
     acoustic_feature_load_process = AcousticFeatureLoadProcess()
diff --git a/train.py b/train.py
index b1a2213..27fd1fb 100644
--- a/train.py
+++ b/train.py
@@ -16,11 +16,12 @@ from functools import partial
 
 parser = argparse.ArgumentParser()
 parser.add_argument('config_json_path', type=Path)
+parser.add_argument('output', type=Path)
 arguments = parser.parse_args()
 
 config = create_from_json(arguments.config_json_path)
-config.train.output.mkdir(exist_ok=True)
-config.save_as_json((config.train.output / 'config.json').absolute())
+arguments.output.mkdir(exist_ok=True)
+config.save_as_json((arguments.output / 'config.json').absolute())
 
 # model
 predictor = create_model(config.model)
@@ -42,7 +43,7 @@ trigger_snapshot = (config.train.snapshot_iteration, 'iteration')
 
 converter = partial(convert.concat_examples, padding=0)
 updater = training.StandardUpdater(train_iter, optimizer, device=config.train.gpu, converter=converter)
-trainer = training.Trainer(updater, out=config.train.output)
+trainer = training.Trainer(updater, out=arguments.output)
 
 ext = extensions.Evaluator(test_iter, model, converter, device=config.train.gpu)
 trainer.extend(ext, name='test', trigger=trigger_log)